With the advent of technologies and services related to teleconferencing and digital image storage, considerable progress has been made in the field of image processing. As will be appreciated by those skilled in the art, image processing typically relates to systems, devices, and methodologies for generating image signal data, compressing the image signal data for storage and/or transmission, and thereafter reconstructing the original image from the compressed image signal data. Critical to any highly efficient, cost effective image processing system is the methodology used for achieving compression.
As is known in the art, image compression refers to the steps performed to map an original image into a bit stream suitable for communication over a channel or storage in a suitable medium. Methodologies capable of minimizing the amount of information necessary to represent and recover an original image are desirable in order to lower computational complexity and cost. In addition to cost, methodologies capable of providing high quality image reproduction with minimal delay are likewise desirable.
Due to the enormous growth potential of businesses relying on these techniques, considerable work and effort has been conducted in this area. Despite these efforts, there still remains a need for an improved image processing method, system, and apparatus that operates to reduce the noise generated during image signal compression (quantization noise), improve the achievable signal to noise ratio (quality) during image reconstruction, while avoiding the lengthy delays typically associated with prior art approaches.